### Abstract

Original language | English |
---|---|

Place of Publication | Tilburg |

Publisher | Operations research |

Number of pages | 25 |

Volume | 2009-3 |

Publication status | Published - 2009 |

### Publication series

Name | CentER Discussion Paper |
---|---|

Volume | 2009-3 |

### Fingerprint

### Keywords

- Uncertainty modeling
- Risk analysis
- Robustness and sensitivity analysis
- Simulation
- Bootstrap

### Cite this

*Methodology for Determining the Acceptability of Given Designs in Uncertain Environments*. (CentER Discussion Paper; Vol. 2009-3). Tilburg: Operations research.

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**Methodology for Determining the Acceptability of Given Designs in Uncertain Environments.** / Kleijnen, J.P.C.; Pierreval, H.; Zhang, J.

Research output: Working paper › Discussion paper › Other research output

TY - UNPB

T1 - Methodology for Determining the Acceptability of Given Designs in Uncertain Environments

AU - Kleijnen, J.P.C.

AU - Pierreval, H.

AU - Zhang, J.

N1 - Subsequently published in European Journal of Operational Research, 2011 Pagination: 25

PY - 2009

Y1 - 2009

N2 - Managers wish to verify that a particular engineering design meets their require- ments. This design's future environment will differ from the environment assumed during the design. Therefore it is crucial to determine which variations in the envi- ronment may make this design unacceptable. The proposed methodology estimates which uncertain environmental parameters are important (so managers can become pro-active) and which parameter combinations (scenarios) make the design unac- ceptable. The methodology combines simulation, bootstrapping, and metamodeling. The methodology is illustrated through a simulated manufacturing system, includ- ing fourteen uncertain parameters of the input distributions for the various arrival and service times. These parameters are investigated through sixteen scenarios, selected through a two-level fractional-factorial design. The resulting simulation In- put/Output (I/O) data are analyzed through a first-order polynomial metamodel and bootstrapping. A second experiment gives some outputs that are indeed un- acceptable. Polynomials fitted to the I/O data estimate the border line (frontier) between acceptable and unacceptable environments.

AB - Managers wish to verify that a particular engineering design meets their require- ments. This design's future environment will differ from the environment assumed during the design. Therefore it is crucial to determine which variations in the envi- ronment may make this design unacceptable. The proposed methodology estimates which uncertain environmental parameters are important (so managers can become pro-active) and which parameter combinations (scenarios) make the design unac- ceptable. The methodology combines simulation, bootstrapping, and metamodeling. The methodology is illustrated through a simulated manufacturing system, includ- ing fourteen uncertain parameters of the input distributions for the various arrival and service times. These parameters are investigated through sixteen scenarios, selected through a two-level fractional-factorial design. The resulting simulation In- put/Output (I/O) data are analyzed through a first-order polynomial metamodel and bootstrapping. A second experiment gives some outputs that are indeed un- acceptable. Polynomials fitted to the I/O data estimate the border line (frontier) between acceptable and unacceptable environments.

KW - Uncertainty modeling

KW - Risk analysis

KW - Robustness and sensitivity analysis

KW - Simulation

KW - Bootstrap

M3 - Discussion paper

VL - 2009-3

T3 - CentER Discussion Paper

BT - Methodology for Determining the Acceptability of Given Designs in Uncertain Environments

PB - Operations research

CY - Tilburg

ER -